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0.463764 | e5d2a1cc401b453b86dca140620b0fa5 | Subunit composition and single-channel activity of wild-type and βAnc-containing acetylcholine receptors.a Subunit stoichiometry and arrangement of the human adult muscle-type acetylcholine receptor (muscle-type AChR; top), where the agonist-binding sites at the α-δ and α-ε subunit interfaces are indicated with asterisks (*). A reconstructed ancestral β-subunit (βAnc; purple) forms hybrid acetylcholine receptors (βAnc hybrid AChR; middle) where βAnc substitutes for the human β-subunit (β; orange) and supplants the human δ-subunit (δ; green). For this to happen, the principal (+) and complementary (–) interfaces of βAnc must be compatible with each other, as well as with the corresponding interfaces of their bracketing α-subunits (red highlights). βAnc also forms homomers (bottom; boxed), which open spontaneously (no agonist), and whose single-channel activity in the presence of agonist mirrors that of the muscle-type acetylcholine receptor. Recordings were obtained in the cell-attached patch configuration with a constant applied potential of –120 mV and filtered with a 5 kHz digital Gaussian filter. Unless otherwise indicated, all recordings were acquired in the presence of 60 μM acetylcholine, where openings represent inward cation currents, and are shown as upward deflections. The scale bar (20 ms, 10 pA) aligned to the top trace applies to all traces. b The compatibility of βAnc with bracketing α-subunits in hybrid AChRs predicts that α/βAnc heteromers are viable. | PMC10076327 | 41467_2023_36770_Fig1_HTML.jpg |
0.45639 | ff4b8f1def02430ca9b13d97c68ddb17 | The human α-subunit and βAnc can coassemble to form viable heteromeric channels that open spontaneously.a Relative cell-surface binding of [125I]-α-bungarotoxin (α-Btx) to cells transfected with the full complement of cDNAs encoding the human adult muscle-type acetylcholine receptor subunits (WT; white), the α-subunit alone (α; darkest grey), βAnc alone (βAnc; light grey), or a 1:1 (by weight) mixture of the α-subunit and βAnc (1:1; intermediate grey). Bar graphs represent the mean of two or three replicates (shown) from independent transfections, normalised to WT. b Frequency of spontaneous bursts of openings from cells transfected with cDNA encoding βAnc alone (0:1; light grey), or with increasing amounts of human α-subunit cDNA (1:1, 10:1; by weight; intermediate and dark grey, respectively), while the amount of βAnc cDNA is kept constant. Bar graphs represent the mean burst frequency averaged across ten separate single-channel patches (individual data points shown in each case), from at least three independent transfections. Difference between mean burst frequency is statistically significant (asterisks), as determined by one-way ANOVA (Tukey’s multiple comparison test; α level of 0.05; 0:1 vs. 1:1, p = 0.0015; 1:1 vs. 10:1, p = 0.0247). c Single-channel burst behaviour of patches from cells transfected with different ratios (0:1, 1:1, 10:1; by weight) of α-subunit and βAnc cDNA. In the absence of agonist, recordings were obtained in the cell-attached patch configuration with an applied potential of –120 mV and filtered with a 5 kHz digital Gaussian filter. In each case, openings are upward deflections, with the scale bar (2 s, 10 pA) beside the bottom trace applying to all zoomed out traces, and the inset boxes themselves representing 40 ms and 25 pA. d Burst duration histograms (see Methods) were manually fit (solid line) with a minimum sum of exponential components (dashed lines; labelled i and ii) containing the types of openings shown inset in c. Note that the dashed lines in the top panel are hidden by the solid line, as there is only a single exponential component that overlaps perfectly with the overall fit. | PMC10076327 | 41467_2023_36770_Fig2_HTML.jpg |
0.419928 | a1e38828bf1842ac82bbb432c4dee3fa | Electrical fingerprinting reveals the contribution of α-subunits to the apparent repression of spontaneous single-channel activity.a Co-transfection of a cDNA encoding the human α-subunit harbouring reporter mutations that reduce single-channel conductance (αLC) with cDNA encoding βAnc leads to reduced spontaneous activity, where b the amplitude and duration of single-channel events is variable. Indicated openings in (a; i–v) are shown expanded in b, with sight-lines overlaid to indicate the amplitudes of individual events. Openings are upward deflections, where the scale bars represent 1 s and 10 pA in a, and 10 ms and 10 pA in b. c Combining single-channel bursts from multiple recordings (see also Fig. S3) where cells were transfected at different cDNA ratios (by weight) shows how single-channel amplitudes segregate into three well-defined amplitude classes (overlaid gaussians; solid lines), where each amplitude class corresponds to openings from channels incorporating either 0, 1, or 2 αLC-subunits. Plotting the amplitude of individual bursts as a function of their duration reveals an apparent correlation (inset 1). d Dwell time analysis of selected bursts whose amplitude is within 1.5 standard deviations of the mean of each amplitude class (shaded regions from inset 2 in c) reveals the contribution of each successive αLC-subunit (dark grey subunits in schematics) to open (left) and burst (middle) durations, as well as in determining the number of successive openings occurring in each burst (right). The traces under the schematics (left) show openings (upward deflections) representative of each exponential component from visual fits of their corresponding duration histograms (right). Scale bar beside the bottom trace in d represents 5 ms and 10 pA. Recordings were obtained in the cell-attached patch configuration with an applied potential of –120 mV and filtered with a 5 kHz digital Gaussian filter. | PMC10076327 | 41467_2023_36770_Fig3_HTML.jpg |
0.463444 | 43fd2747f6354e80a286418ec0ff6c7f | Agonist relieves apparent repression of α/βAnc heteromers.Single-channel activity from cells expressing a βAnc homopentamers (0:1; α:βAnc cDNA; by weight) and b α/βAnc heteromers (10:1) in the absence (–) and presence (+) of 300 μM acetylcholine. Recordings were obtained in the cell-attached patch configuration with an applied potential of –120 mV and Gaussian filter of 5 kHz. Single-channel openings represent inward cation currents, and are shown as upward deflections. The scale bar beside the bottom trace in b applies to all traces and represents 1 s and 10 pA. c Comparison of burst frequency in paired recordings from cells expressing either βAnc homopentamers (0:1), or α/βAnc heteromers (10:1). In each case, paired cell-attached recordings from the same cell were acquired first in the absence (–), and then in the presence (+), of 300 μM acetylcholine in the patch pipette. Box plots represent one standard deviation from the mean, with the internal horizontal line denoting the mean of the 10 recordings in each case. Maximum and minimum values are presented as box plot whiskers. As determined by a two-way ANOVA, the difference between mean burst frequency –/+ 300 μM acetylcholine is statistically significant (α level of 0.05) for the α/βAnc heteromers (10:1, p = 0.0011; asterisk), but not the βAnc homopentamers (0:1, p = 0.7189; ns). | PMC10076327 | 41467_2023_36770_Fig4_HTML.jpg |
0.453203 | 55346f0806a14aaeb669e3c1c52c31ac | Parallels between induction of gene expression and agonism in a pentameric ligand-gated ion channel.a Constitutive expression of a gene (top) can be repressed by the binding of a repressor (yellow protein) to an operator sequence (middle), which can then be derepressed by the binding of an inducer (orange circle) to the repressor (bottom). b Constitutive activity of a pentameric ion channel (top; purple βAnc) can be repressed by incorporation of a repressor protein (middle; yellow α-subunits), which can then be derepressed by the binding of an inducer (bottom; orange agonist). | PMC10076327 | 41467_2023_36770_Fig5_HTML.jpg |
0.445084 | 0de8dc2f81d840d482cbc3e485256561 | Treatment of mice with the EV inhibitor Calpeptin affects the in vivo production of EVs carrying p-Smad2.A Procedure followed to treat C57BL/6J mice with Calpeptin in order to analyze EVs in BM. B NTA quantification of EVs isolated from mice BM at day 20. Data showing that Calpeptin reduced the number of EVs in BM by ~26%, n = 5 mice per group. C Size of EVs measured by NTA. D ELISA quantification of EVs showing a reduction in the detection of p-Smad2/3. Quantification was normalized to 109 particles, n = 4 mice per group. E Western blot with 50 µg of proteins extracted from EVs, n = 3 mice per group. Data showing the presence of p-Smad2 and Smad2, but not p-Smad3 and Smad3. Flotillin 1 (Flot1) generally detected on EVs was used as an endogenous control. F Quantification of the Western blots. On this figure, data are shown as means ± SD. P value measured by two-tailed unpaired Student’s t test; *P < 0.05; **P < 0.01; ****P < 0.0001; ns, non-significant. | PMC10076352 | 41420_2023_1414_Fig1_HTML.jpg |
0.463831 | f7183b0a5cf245dea45738b218eccb3c | Treatment of mice with the EV inhibitor Calpeptin affects maintenance of HSC in vivo.A Flow cytometry on Lin- cells showing that a treatment with Calpeptin decreased the percentage of hematopoietic progenitors (LSK cells) as well as HSC (SLAM cells), n = 5 mice per group. B Mean fluorescence intensity (MFI) measured by flow cytometry on HSC (SLAM cells), after cell permeabilization, showing a loss of p-Smad2/3 following treatment with Calpeptin, n = 5 mice per group. C Flow cytometry showing a reduction in quiescent HSC (in G0) following treatment with Calpeptin, n = 5 mice per group. D CFU assay on semi-solid media showing a reduction in the number of total CFU per 105 Sca1+ cells, isolated from the BM of mice treated with Calpeptin. CFU were observed after 8 days of ex vivo culture, n = 4 mice per group. E Distribution among the CFU showing a reduction of the less differentiated progenitors (CFU-GEMM and CFU-GM), as well as an increase in mono-lineage progenitors (CFU-G and CFU-M) among Sca1+ cells isolated from the BM of mice treated with Calpeptin. F Analysis of the reconstitution capacity in vivo following the i.v. transplantation of 4 × 105 Sca1+ cells freshly isolated from donor C57BL/6SJL (Ly.1) mice treated or not with Calpeptin, in C57BL/6J (Ly.2) recipient mice, n = 5 mice per group. Reconstitutions were assessed on WBC in PB, as well as on LSK cells after Lin- depletion of BM cells, 16 weeks after transplantation. Examples of cytometry plots for LSK cells and statistics for LSK cells and WBC. On this figure, data are shown as means ± SD. P value measured by two-tailed unpaired Student’s t test; **P < 0.01; ***P < 0.001; ****P < 0.0001. | PMC10076352 | 41420_2023_1414_Fig2_HTML.jpg |
0.452081 | 76bbc2538d5841259cb1f00e18d39064 | MS-5 cells produce EVs carrying p-Smad2 that are uptaken by HSC.A Procedure followed to produce EVs-DMSO or EVs-SB431542 with MS-5 cells. B NTA quantification and size of EVs isolated from the supernatant of MS-5 cells treated with the TGF-β type I receptor kinase (ALK5) inhibitor (EVs-SB431542) or not treated (EVs-DMSO). Data are shown as means ± SD, n = 6 biological samples. C ELISA showing the presence of p-Smad2/3 in MS-5 EVs. Treatment with SB431542 abrogated the production of p-Smad2/3 in EVs. Low production of the active TGF-β1 ligand in EVs was also detected by ELISA. Quantification was normalized to 109 particles, n = 4 biological samples. D Western blot showing the production of p-Smad2 in MS-5 cells and EVs. The co-Smad4 protein was only detected in MS-5 cells, not in EVs. MS-5 cells showed an absence of p-Smad3, which was also not detected in EVs. Treatment with SB431542 abrogated the presence of p-Smad2, both in MS-5 cells and in EVs (EVs-SB431542). On this figure, data are shown as means ± SD. P value measured by two-tailed unpaired Student’s t test; ****P < 0.0001; ns, non-significant. | PMC10076352 | 41420_2023_1414_Fig3_HTML.jpg |
0.418992 | bde3686c63814e75af922dc27367b177 | MS-5 cells produce EVs carrying p-Smad2 that can be uptaken by HSC.A Procedure followed to treat Lin- and Sca1+ cells with PKH67+ EVs-DMSO or EVs-SB431542. We administered 109 particles per 106 Lin- cells, or 109 particles per 4 × 105 Sca1+ cells. B Microscopy on a 96-well round bottom plate and flow cytometry, after the exposure of Lin- cells during four hours with PKH67+ EVs. Data showing that ~11% of the Lin- cells bound PKH67+ EVs. Magnification ×4, black scale bar corresponds to 100 µm. C Flow cytometry on PKH67- and PKH67+ gated Lin- cells showing that PKH67+ EVs bound more to HSPC (LSK; Lin- Sca1+ c-Kit+ cells). D Sca1+ cells were freshly isolated from the BM of mice (fresh) and treated with EVs-DMSO, EVs-SB431542 or without EVs (w/o EVs) for four hours. Flow cytometry showing the uptake of PKH67+ EVs by >80% of the Sca1+ c-Kit+ cells, as well as >80% of HSC (SLAM cells). Data are shown as means ± SD, n = 4 biological samples. P value calculated against the fresh conditions and measured by one-way ANOVA with Tukey’s multiple comparison test; ****P < 0.0001; ns, non-significant. E Fluorescent optical sections, showing the uptake of PKH67+ EVs in the cytoplasm and nucleus of HSC (SLAM cells), purified by FACS, four hours after incubation with EVs-DMSO or EVs-SB431542. Magnification ×63, black scale bar corresponds to 10 µm, white bars correspond to the sections for measurement of the PKH67 green fluorescence and DAPI. | PMC10076352 | 41420_2023_1414_Fig4_HTML.jpg |
0.401206 | 224bb258e22e4df3883b6deda2af6112 | MS-5-EVs carrying p-Smad2 allow maintenance of HSC ex vivo.A Procedure followed to maintain Sca1+ HSC freshly (fresh) isolated ex vivo, with MS-5-EVs carrying p-Smad2 or not due to a treatment of MS-5 cells with SB431542. We administered 109 particles per 4 × 105 Sca1+ cells for 48 h. B Fluorescent optical sections, showing high level of p-Smad2 in the nucleus of HSC after incubation with EVs-DMSO, while HSC treated with EVs-SB431542 showed a low intracellular level of p-Smad2. Magnification ×63, white scale bar corresponds to 10 µm, white bars correspond to the sections for measurement of p-Smad2 and DAPI fluorescence. PKH67+ SLAM cells were purified by FACS. C Flow cytometry on HSC (SLAM cells) after permeabilization showing that treatment with EVs-DMSO maintained p-Smad2/3 levels, while a decrease in active TGF-β signaling was observed with EVs-SB431542, as well as without EVs (w/o EVs). Data normalized to the same number of HSC. D Treatment with EVs-DMSO maintained the number of HSC (SLAM cells) after 48 h, while EVs-SB431542 induced their exhaustion. E Cell cycling activity of HSC, measured by flow cytometry after permeabilization, showing maintenance of quiescent HSC (Ki67- SLAM cells in G0) following treatment with EVs-DMSO, but not with EVs-SB431542. In this figure, data are shown as means ± SD, n = 4 mice. P value calculated against the fresh condition and measured by one-way ANOVA with Tukey’s multiple comparison test; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, non-significant. | PMC10076352 | 41420_2023_1414_Fig5_HTML.jpg |
0.467221 | 3cf2a6f074f34a918d555b3e21b7faf2 | Transplantation of HSC, maintained ex vivo with MS-5-EVs carrying p-Smad2.A Procedure followed to maintain Sca1+ HSC ex vivo for 48 h with EVs-DMSO or EVs-SB431542. B Analysis of the reconstitution capacity in vivo following the i.v. transplantation of 4 × 105 Sca1+ cells in C57BL/6J (Ly.2) recipients, n = 4 mice per group. Sca1+ cells isolated from donor C57BL/6SJL (Ly.1) mice were freshly injected (fresh) or exposed to EVs ex vivo for 48 h before the transplantation. We assessed the reconstitution 16 weeks after the transplantation on LSK cells in BM, as well as on WBC in PB. Examples of cytometry plots for LSK cells, statistics on LSK cells, and WBC. Data are shown as means ± SD, n = 4 mice. P value calculated against the fresh condition and measured by one-way ANOVA with Tukey’s multiple comparison test; ****P < 0.0001; ns, non-significant. C UMAP data frame showing distribution among CD45.1 positive WBC in different hematological lineages (B-lymphocytes, T-lymphocytes, myeloid cells, and natural killer cells). Data showing that Sca1+ cells treated ex vivo with EVs-DMSO for 48 h were able to reconstitute hematopoiesis in all lineages in secondary recipient mice, and to a level that was similar to fresh Sca1+ cells. Data are shown as means ± SD, n = 4 mice. P value measured by two-tailed unpaired Student’s t test; ns, non-significant. | PMC10076352 | 41420_2023_1414_Fig6_HTML.jpg |
0.442783 | 423dbb1879df44a2abf23f3c4c80eaa2 | BM-derived EVs carry the TGF-β signal transducer Smad2 for the homeostasis of HSC.Schematic illustration of the proposed mechanism involving EVs produced by MSC that carry the cargo p-Smad2 involved in the quiescence and maintenance of HSC. | PMC10076352 | 41420_2023_1414_Fig7_HTML.jpg |
0.445329 | edb96029901a409398e891c62642706a | Most common procedures by consultation modality (in-person or telehealth). The light gray represents the number of patients in the in-person cohort, and the dark grey represents the number of patients in the telehealth cohort. | PMC10076909 | gr1_lrg.jpg |
0.475643 | f5ecad888deb45ccabada7df4709f8bf | Optimized structures of PyDev using DFT method. PyDev indicates pyridine derivatives. | PMC10076986 | 10.1177_11779322221146651-fig1.jpg |
0.476148 | 631098c14aa24aaba298cef6c7634fac | Structure of positive reference drugs: (A) remdesivir and (B) hydroxychloroquine. | PMC10076986 | 10.1177_11779322221146651-fig2.jpg |
0.429189 | 6ff3d860b01a453599957e4a263b8937 | (A) Docking analysis (using AutoDock) of PyDev (12-ligands) and two standard drugs with (6LU7) targets of Coronavirus. (B) Docking Analysis (using AutoDock) of PyDev (12-ligands) and two standard drugs with (6VSB) targets of Coronavirus. (C) Docking Analysis (using AutoDock) of PyDev (12-ligands) and two standard drugs with (6VXX) targets of Coronavirus. (D) Docking Analysis (using AutoDock) of PyDev (12-ligands) and two standard drugs with (6VW1) targets of Coronavirus. PyDev indicates pyridine derivatives. | PMC10076986 | 10.1177_11779322221146651-fig3.jpg |
0.451807 | 95f9716edeff439db63f498711692dc8 | XRD patterns of nano-BaTiO3 ((A) full range; (B) in the 2θ range of 44.0–47.0°). | PMC10077948 | d2ra08334e-f1.jpg |
0.473734 | 3ec43a30d4bb4a3e8b3fd04b8d8370da | Raman spectra of BaTiO3-N and BaTiO3-IL-5. | PMC10077948 | d2ra08334e-f2.jpg |
0.433573 | 27b6f5a1f35b48e29e47639587ec2dc3 | SEM and TEM images, and particle size distributions, of nano-BaTiO3. SEM: A1, BaTiO3-N; A2, BaTiO3-IL-1; A3, BaTiO3-IL-3; A4, BaTiO3-IL-5. TEM: B1, BaTiO3-N; B2, BaTiO3-IL-1; B3, BaTiO3-IL-3; B4, BaTiO3-IL-5. Size distributions: C1, BaTiO3-N; C2, BaTiO3-IL-1; C3, BaTiO3-IL-3; C4, BaTiO3-IL-5. | PMC10077948 | d2ra08334e-f3.jpg |
0.478468 | 0f2d96663c2d4f16846a3a7500f5cbfd | Effect of ILs loadings on dielectric constant and dielectric loss of BaTiO3 ceramics at different temperature. | PMC10077948 | d2ra08334e-f4.jpg |
0.474519 | 14d6b669b15d49429a260b7580cec1b2 | XRD patterns of BaTiO3-B and BaTiO3-U ((A) full range; (B) in the 2θ range of 44.0–47.0°). | PMC10077948 | d2ra08334e-f5.jpg |
0.399493 | d8cd33864f7b41a9acf0ca8df15d4eec | SEM images of BaTiO3-U (A) and BaTiO3-B (B). | PMC10077948 | d2ra08334e-f6.jpg |
0.435772 | c2e1cddaf71041b8a53a10f0c00f8e53 | Temperature-dependence of the dielectric constant and dielectric loss of BaTiO3 ceramics with different morphologies. | PMC10077948 | d2ra08334e-f7.jpg |
0.502001 | 929d8724a66e48c8b27b652cb3c34632 | Our meta-learning model’s parameters θ are trained over a distribution of source cancer types, and the corresponding loss L are generated. θ are optimized by gradient descent, or back-propagation of ∇Ltaski | PMC10079355 | btad113f1.jpg |
0.457029 | eda0204527314e4abd8acc4f28c7cb5c | The process of studying the correlation between genes with similarly high DeepLIFT contribution scores and their likelihood of being enriched together in the same STRING enrichment sets | PMC10079355 | btad113f2.jpg |
0.462656 | 870d55968a6841488383e1471ea25a8f | (A) Symptomatology of supratentorial/midline (central) tumors of childhood (3). (B) Comparison of brain tumor symptomatology for those with and without NF1 (11). (C) Comparison of anatomical distribution of OPHG between sporadic and NF1 types using the Modified Dodge Classification/PLAN Score (42). (D) Anatomical distribution of NF1 OPG in the multi-centre NF1 clinic cohort (84). | PMC10080591 | fped-11-1038937-g001.jpg |
0.42426 | d29bd63090b74d098cfacc55bbe9ae94 | MRI scan of typical (A) sporadic hypothalamic and (B) multi-focal NF1 OPHG involving posterior radiations; (C) clinical specialisms involved in the OPHG multidisciplinary team. | PMC10080591 | fped-11-1038937-g002.jpg |
0.485434 | 62311f461bc5495ab24ea31b4840b503 | (A) Patient selection criteria for observation vs. treatment in SIOP LGG 2 (004 randomised trial (17). (B) Comparison of LogMAR visual acuity results from SIOP LGG 2004 workshop comparing pre- and post- bilateral visual acuity for observation (top green graphs) and treatment (lower orange graphs) with vincristine and carboplatin in patients with NF1 (46). | PMC10080591 | fped-11-1038937-g003.jpg |
0.390614 | 652c611e2a494b0d9ed06ebd5538e994 | (A) A matrix of patient characteristics including visual acuity (LogMAR scores for one/both eyes), PLAN stage ¾ +/− (optic radation involvement) and age at diagnosis, (B): consensus (>70%) voting for 25 NF1 OPHG patient histories reported within the matrix identifying cases selected for initial observation (O), treatment (T) or? randomisation (?). (C) Spider plot of primary reason for consensus judgement for O,T & R. (D) Table of clinical reasons supporting strategy selection for O,T & R (51). | PMC10080591 | fped-11-1038937-g004.jpg |
0.419271 | 6729212463a24513878a06015a668496 | Evidence-based multi-disciplinary factors to be considered for selection of treatments (surgery, chemotherapy or radiotherapy) vs. observation in OPHG of infancy and childhood in OPHG Adapted from (3, 46, 79). | PMC10080591 | fped-11-1038937-g005.jpg |
0.417817 | 667ccd044541467eb2a77b24ffa73915 | Cluster analysis dendrogram applied to the interviewees’ speeches, Macaé
– RJ, Brazil, 2021. | PMC10081592 | 1980-220X-REEUSP-56-e20210537-gf01.jpg |
0.431016 | 0fd70ae4df9049b5a4f4c7003b078f43 | LNT treatment suppresses spontaneous diabetic frequency in NOD mice.Pre-diabetic female NOD mice 8 weeks of age received intraperitoneal treatment with 5 mg/kg LNT in 100 μL PBS (LNT) or only 100 μL PBS (Ctrl) as a control every other day for 16 weeks, followed by an evaluation of T1D development. Hyperglycaemia in mice was measured weekly, and two consecutive weeks of a glucose level >250 mg/dL was considered indicative of diabetes. A The frequency of mice without T1D over time (n = 15). B Representative history pancreas slices from mice in (A). Pancreatic islets are indicated by white arrows. C The percentages of islets with varying grades of insulitis (n = 20). The stages (0–4) represent diabetes progression (also suits for F and I). NOD mice with 140–160 mg/dL blood glucose levels underwent intraperitoneal treatment with 5 mg/kg LNT before assessment of diabetes progression. D Blood glucose levels in mice over time (n = 5). E Representative histology pancreas slices from the mice in (D). Pancreatic islets are indicated by white arrows. F The frequency of islets with grade 0–4 insulitis (n = 20). NOD mice with 200–230 mg/dL blood glucose received an intraperitoneal treatment with 5 mg/kg LNT before regular monitoring of the diabetes progression. G Blood glucose levels in mice over time (n = 5). H Representative histology pancreas slices from the mice in (G). Pancreatic islets are indicated by white arrows. I The frequency of islets with grade 0–4 insulitis (n = 20). Summary data are presented as the mean ± SEM. *p < 0.05, **p < 0.01 vs the Ctrl group. | PMC10082833 | 41387_2023_233_Fig1_HTML.jpg |
0.506186 | e6fbaa1ba6dd44d6a7e44432dc707383 | LNT diminishes autoreactive T cells but elevates Treg in NOD mice.Female NOD mice received an intraperitoneal treatment with 5 mg/kg LNT every other day beginning at 8 weeks of age, followed by euthanasia at 24 weeks of age. Manifest CD25 + Foxp3+ Treg cells (A), CD4 + IFN-γ + T cells (B) and CD8 + IFN-γ + T cells (C) frequencies in mice spleens and PnLNs. Foxp3+ Tregs, CD4 + IFN-γ + T cells and CD8 + IFN-γ + T cells frequencies in spleens (D), PnLNs (E) and pancreases (F) of NOD mice with 140–160 mg/dL blood glucose levels treated with LNT or Ctrl for 16 weeks, and blood glucose levels in the Ctrl mice reached 400–500 mg/dL. The frequency of Foxp3+ Tregs, CD4 + IFN-γ + T cells and CD8 + IFN-γ + T cells in spleens (G), PnLNs (H) and pancreases (I) of NOD mice with 200–230 mg/dL blood glucose levels that were treated with LNT or Ctrl for 4 weeks; the blood glucose levels in Ctrl mice reached 450–500 mg/dL. Summary data are shown as the mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 vs the Ctrl group. | PMC10082833 | 41387_2023_233_Fig2_HTML.jpg |
0.426195 | ea915451ffd84c6e93c5566f37a7ba16 | LNT promotes Treg cell differentiation in vitro.CD4 + CD25- (naive) T cells of the spleens and PnLNs from C57BL/6 mice were incubated with anti-CD3 and anti-CD28 for three days in glucose-free DMEM (Ctrl) encompassing 10% FBS-contained or with 50 μg/mL or 100 μg/mL LNT. Representative FACS images (A) and CD25 + Foxp3+ Treg cell frequency in CD4 + T cells (B) after a three-day incubation. C The absolute numbers of CD25 + Foxp3+ Treg cells. The proportion of cells in the gate was suggested by numbers adjacent to outlines in the FACS images. D, E Foxp3 mRNA levels at 24 h. F, G Absolute numbers of CD4 + CD25-Foxp3- (Non-Treg) cells. All panels report data verified in at least two independent experiments. Summary data are summarised as the mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. | PMC10082833 | 41387_2023_233_Fig3_HTML.jpg |
0.419772 | c51afb0563ed4df6a4f1c4ce46b42700 | Treatment using LNT-induced Treg cells suppresses the diabetogenicity of NOD mice.Subsequent to the purification of Treg cells from euglycemic PBS (Ctrl) or LNT-treated mice (as depicted in Fig. 1A and in splenic T cells isolated 15 days after receiving the final LNT injection), Treg cells were adoptively transferred to female NOD/Ltj mice at 8 weeks (A–C) or 10 weeks (D–F) of age (intravenous; 1 × 105 Treg cells/mouse), followed by weekly monitoring of hyperglycaemia. Mice with two consecutive weeks of 250 mg/dL blood glucose levels were considered to suffer from diabetes. A and D) The frequency of diabetes-free mice over time. B and E Representative histology pancreas slices from the mice in (A) and (D). Pancreatic islets are indicated by white arrows. C and F The frequency of islets with grade 0–4 insulitis from the mice in (B) and (E) (n = 20). Summary data are summarised as the mean ± SEM. **p < 0.01. | PMC10082833 | 41387_2023_233_Fig4_HTML.jpg |
0.453409 | d8d3e277e56b425bab961b958b05a6d5 | Landscape of cuproptosis-related genes and biological characteristics of cuproptosis-related molecular subtypes in BCa.(A) Locations of cuproptosis-related genes on 23 chromosomes. (B) Interaction of cuproptosis-related genes. (C) Correlation analysis between cuproptosis-related genes. Numbers in the square represent correlation coefficients. Crosses in the square represent P > 0.05. (D) Mutation frequencies of cuproptosis-related genes in BCa patients in TCGA. (E) Principal component analysis of cuproptosis-related genes in the combined dataset identified three distinct subtypes. (F) Kaplan–Meier curves for overall survival of combined dataset with the cuproptosis-related subtypes. (G) Differences in clinicopathologic features between three distinct subtypes. BCa, bladder cancer; OS, overall survival; NMIBC, nonmuscle invasive bladder cancer; MIBC, muscle invasive bladder cancer; TCGA, the Cancer Genome Atlas. *, p < 0.01, ∗∗∗, p < 0.001. p value was calculated with t test, except survival analysis was analyzed using a two-sided log-rank test. | PMC10083007 | peerj-11-15088-g001.jpg |
0.420434 | 8e02be6a5c164de7a6c805bd095e1420 | The association of the cuproptosis-related molecular subtypes with cuproptosis score and TIICs.(A) Kaplan–Meier curves of the cuproptosis score in the combined dataset. (B) The association of the cuproptosis score with cuproptosis-related genes. p value was calculated with Pearson correlation. (C) The different levels of cuproptosis scores among cuproptosis-related molecular subtypes. (D) The relative infiltration percentage of 22 TIICs of each BCa patient in the combined dataset. (E) The relative infiltration levels of TIICs based on the cuproptosis-related molecular subtypes. TIICs, tumor-infiltrating immune cells; OS, overall survival; BCa, bladder cancer. *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001. p value was calculated with t test, Bonferroni correction applied for pairwise comparisons. Survival analysis was analyzed using a two-sided log-rank test. | PMC10083007 | peerj-11-15088-g002.jpg |
0.462376 | 7331758473cd42e698370484d056d3f6 | Landscape of biological characteristics of cuproptosis gene cluster.(A) Volcano plot of DEGs differentially expressed between Cluster 1 and Cluster 2/3. (B–C) KEGG and GO enrichment analyses of up-regulated DEGs in Cluster 2/3. (D) Venn diagram of the overlapping prognostic DEGs between TCGA and combined dataset. (E) Principal component analysis of overlapping prognostic DEGs in the combined dataset identified two distinct subtypes. (F) Kaplan–Meier curves of the cuproptosis gene cluster in the combined dataset. (G) The different levels of cuproptosis scores between GeneCluster 1 and GeneCluster 2. (H) Expression of cuproptosis-related genes between GeneCluster 1 and GeneCluster 2. TCGA, the Cancer Genome Atlas; FDR, false discovery rate; DEGs, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes Genomes; GO, Gene Ontology; OS, overall survival. *, p < 0.05, **, p < 0.01, ***, p < 0.001. p value was calculated with t test, except survival analysis was analyzed using a two-sided log-rank test. | PMC10083007 | peerj-11-15088-g003.jpg |
0.468537 | d62ae19e731e469da83bc0702c2ad89d | Development and performance of the cuproptosis-related prognosis signature.(A) Based on the optimal λ value (−2.840), 16 genes were selected. (B) Selecting the optimal number of genes based on minimum partial likelihood deviance in TCGA. (C) Kaplan–Meier curves of the cuproptosis-related prognosis signature in TCGA. (D) Ranked dot and scatter plots showing the risk scores distribution and patient survival status. (E) Principal component analysis of 16 genes in TCGA identified two risk groups. (F) Kaplan–Meier curves of the cuproptosis-related prognosis signature in the combined dataset. (G) Alluvial diagram showing the changes of cuproptosis-related molecular subtype, gene cluster, risk group, cuproptosis score group and survival status. (H) The different levels of risk scores among cuproptosis-related molecular subtypes. (I) The different levels of risk scores between GeneCluster 1 and GeneCluster 2. (J) Differences in clinicopathologic features between two risk groups. TCGA, the Cancer Genome Atlas; OS, overall survival. p value was calculated with t test, Bonferroni correction applied for pairwise comparisons. Survival analysis was analyzed using a two-sided log-rank test. | PMC10083007 | peerj-11-15088-g004.jpg |
0.397746 | 0088a9709de64ebb8cc9b3c0d3ee24c9 | Landscape of biological characteristics of the cuproptosis-related prognosis signature (risk score).(A) The mutation frequency of high risk group. (B) The mutation frequency of low risk group. (C) The different levels of TME between low- and high-risk groups. (D) Correlations between risk score and TMB. (E) The different levels of cuproptosis score between low- and high-risk groups. (F) Correlations between risk score and cuproptosis score. p value and correlation coefficient R were calculated with Pearson correlation. (G) The different IC50 values of chemotherapeutic drugs between low and high risk groups. (H) GSEA analysis of the cuproptosis-related prognosis signature. (I) GSVA analyzed the different biological pathways between low- and high-risk groups. TMB, tumor mutation burden; IC50, semi-inhibitory concentration, GSEA: Gene Set Enrichment Analysis; GSVA, Gene Set Variation Analysis. *, p < 0.05, **, p < 0.01, ***, p < 0.001. p value was calculated with t test. | PMC10083007 | peerj-11-15088-g005.jpg |
0.445467 | 7c9a5921399a45ddad349fcb9a57ce7f | The correlation between the cuproptosis-related prognosis signature (risk score) and TME characteristics.(A) The relative infiltration levels of TIICs based on the risk groups. (B) The association of the risk score with the infiltration level of TIICs. p value was calculated with Pearson correlation. (C) The expression of immune checkpoints based on the risk groups. (D) The association of the risk score with the expression of immune checkpoints. p value was calculated with Pearson correlation. (E) The different levels of TME score between low- and high-risk groups. (F) The different levels of TIDE score between low- and high-risk groups. (G) Proportions of immunotherapy response in high- and low-risk groups. p value was calculated with Chi-square test. (H) The TIDE value of each BCa patient based on low- and high-risk groups. (I) GSEA analysis of the cuproptosis-related prognosis signature. TME, tumor microenvironment; TIICs, tumor-infiltrating immune cells; TIDE, Tumor immune dysfunction and exclusion; GSEA, Gene Set Enrichment Analysis. *, p < 0.05, **, p < 0.01, ***, p < 0.001. p value was calculated with t test except Chi-square test in (G). | PMC10083007 | peerj-11-15088-g006.jpg |
0.480073 | 3760e04682fb41839ae47e4cb34027e7 | The construction and performance of the nomogram in TCGA.(A) Univariate and multivariate Cox analyses of the cuproptosis-related prognosis signature and other clinicopathological features. (B) Nomogram for predicting the probability of 1-, 3-, and 5-year OS. (C) Proportions of survival status in BCa patients ≥ T2 stage & high risk group and other patients. (D) ROC curves of the cuproptosis-related prognosis signature and other clinicopathological features for prognostic prediction. e ROC curves to predict the 1-, 3- and 5-year OS according to the nomogram. (F–H) Calibration plots of the nomogram for predicting the probability of 1-, 3-, and 5-year OS. (I–K) DCA of the nomogram predicting 1-, 3-, and 5-year OS. TCGA, the Cancer Genome Atlas; OS, overall survival; BCa, bladder cancer; ROC, receiver operating characteristic curve; DCA, decision curve analysis. p value was calculated with Chi-square test, except survival analysis was analyzed using univariate and multivariate Cox analysis. | PMC10083007 | peerj-11-15088-g007.jpg |
0.435354 | 45140928e7b04bfb9989f4749c9fe031 | Validation of cuproptosis-related genes through in vitro experiments.*, p < 0.05; **, p < 0.01; ***, p < 0.001, p value was calculated with t test, compared to control group (SV- HUC-1). The data represent the mean ±s.e.m of three replicate experiments. | PMC10083007 | peerj-11-15088-g008.jpg |
0.395503 | e456ab4114764ded90c824a9fde7b204 | Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flow diagram. | PMC10083111 | jnm-29-2-132-f1.jpg |
0.401863 | 4a97c8f8e8ea47408c18059cd082192b | Forest plot of studies showing prevalence of small intestinal bacterial overgrowth in systemic sclerosis-patients (39.9% [95% CI, 33.1-47.1]; I2 = 76.00%; P < 0.001). | PMC10083111 | jnm-29-2-132-f2.jpg |
0.472298 | ebed1df52d8440f19921916b9b4ac18a | Forest plot of studies showing prevalence of small intestinal bacterial overgrowth (SIBO) in systemic sclerosis-patients and controls, stratified according to mode of diagnosis of SIBO (OR, 9.6; 95% CI, 5.6-16.5; P < 0.001), (I2 = 0.00%, P = 0.798). The odds ratio for SIBO in SSc-patients compared to controls utilizing jejunal aspirate and culture (JAC) is 9.0 (95% CI, 2.7-30.4; P < 0.001), (I2 = 0.00%, P = 0.985), utilizing lactulose breath test (LBT) is 12.0 (95% CI, 6.1-23.6; P < 0.001), (I2 = 0.00%, P = 0.404), utilizing glucose breath test (GBT) is 4.1 (95% CI, 1.0-16.3; P = 0.041), (I2 = 0.00%, P > 0.999). | PMC10083111 | jnm-29-2-132-f3.jpg |
0.414418 | cfb36e6e64af44728ac3811a0646a9f0 | ScRNA-seq reveals dynamic changes during sex differentiation in orange-spotted grouper gonads | PMC10083225 | zr-44-2-269-1.jpg |
0.425358 | c4e17cf2c12a4d88997c1d22523ba49e | Schematic diagram of intervertebral disc height index (DHI) measurement. DHI was the ratio of intervertebral disc height (bc) to upper vertebral body height (ab). | PMC10083248 | fsurg-10-1146893-g001.jpg |
0.471879 | c08f2f2e187f47978d255e10d32a2c9a | Flow chart of patient selection process. | PMC10083248 | fsurg-10-1146893-g002.jpg |
0.391958 | fa3535cfe88f4361beeff51149e52a9d | A 45 years female patient diagnosed with lumbar spinal stenosis underwent posterior PEEK rods hybrid surgery with fusion procedure at the L4/5 level and non-fusion procedure at the L5/S1 level. Preoperative anterior-posterior and lateral fluoroscopy was showed in (A,B), while postoperative anterior-posterior and lateral fluoroscopy at the final follow-up was showed in (C,D). Compared preoperative sagittal MRI scans (E) with sagittal MRI scans at the final follow-up (F), it was found that intervertebral disc degeneration improved from Grade 4 to Grade 3 according to Pfirrmann Classification. The CT reconstruction confirmed that the bilateral PEEK rods were intact at the final follow-up (G,H). | PMC10083248 | fsurg-10-1146893-g003.jpg |
0.404015 | 4482622a839e44d7bbf791a9c4204196 | Role of the microbiota‐gut‐brain axis and the immune system in depression. In immune‐related depression, the stress response and the immune system are dysregulated; microglia are abnormally activated and there is an increased level of inflammatory cytokines in circulation and in the brain. Patients with depression display altered gut microbiota composition and diversity compared with healthy participants. Current pharmacological treatments for immune‐related depression include traditional antidepressants and anti‐inflammatory drugs. On the other hand, lifestyle factors such as exercise and diet are considered excellent adjunctive therapies for antidepressant action, which can influence the gut microbiome and the immune system. Future clinical approaches to combat depression may involve microbiota‐directed strategies such as probiotics, prebiotics and FMT. FMT, fecal microbiota transplant; PRE, prebiotics; PRO, probiotics. | PMC10084001 | CPT-113-246-g001.jpg |
0.405778 | d2068dcbd256453183e949f9df955975 | Research flow-diagram (Based on Consort 2010 flow diagram. http://www.consort-statement.org/consort-statement/flow-diagram) | PMC10084687 | 40359_2023_1154_Fig1_HTML.jpg |
0.404153 | b97e0d26eddc4a46bd5e587da780715f | RNA editing in coding sequences is exceptionally high in arteries.(a) Coding Editing Index of all GTEx samples, presenting the editing level per donor as a weighted average over 314 coding editing sites. (b) Clustering tissues by the profile of editing levels for the 314 sites (calculated for pooled GTEx data). Columns correspond to editing sites meeting cutoff values of ≥ 5% editing and expression in at least five tissues. Colors represent the editing percent at each site. The values correspond to the pulled average per site for all samples meeting the specified cutoffs for each site. Arrows indicate the positions of IGFBP7, FLNA, NEIL1, CCN1 and SRP9, the sites where most cardiovascular editing takes place. (c) The relative contribution of specific coding sites to the overall recoding activity. Notably, all highly edited sites are recoded (editing causes an amino-acid change) and evolutionarily conserved across mammals—samples from left ventricles of unselected GTEx donors. | PMC10085048 | pcbi.1010923.g001.jpg |
0.381318 | aa097c930f484929b8bd4c23cca12ed6 | RNA-editing in Alu sequences in atherosclerosis and cardiomyopathies.AEI demonstrates consistently increased editing levels of all Alu sequences in (a) atherosclerosis (ASCVD: red; controls: White; Cerebrovascular: yellow) and (b) CMPs (Patients: red; Controls: white) patients, and hypo-editing in cerebrovascular patients. The DCM and ICM groups are compared to the same control group. Note that due to differences in read length, the nominal index values cannot be compared across the two panels. The exact p-values are detailed in Tables 1 and 2. | PMC10085048 | pcbi.1010923.g002.jpg |
0.497819 | 1483e55d66ae4b4a97fe5f08d6fc8fab | Interferon stimulated genes and ADAR1 expression in CMPs.Interferon Signature (ISG) Score in (a) CMPs and (b) ICM patients. ADAR1 expression levels in transcript per million units in patients with (c) CMPs and (d) ICM. The exact p-values are detailed in Tables 1 and 2. | PMC10085048 | pcbi.1010923.g003.jpg |
0.453512 | a5cb58c597dc478fb758db0927b153b1 | The landscape of coding editing in cardiovascular patients.Coding Editing Index distribution in (a) Aortae of cerebrovascular and (b) ASCVD patients. (c) Heatmap summarizing all significant (FDR cutoff of ≤ 0.05) and meaningful (editing index difference ≥ 5%) coding editing sites in cardiovascular tissues from GTEx data. Columns are editing sites. Rows represent individual samples of cardiovascular tissue taken from donors with either cardiac or cerebral disease. The heatmap presents 139 patients who have information for at least 70 editing sites. We calculated the change in editing levels for each patient in each site by subtracting the control group average at that site. The color represents the direction of change (blue, elevated editing levels; red, reduced editing levels). (d) Summary of the significant changes in editing in the cardiomyopathies cohorts. Columns are editing sites that differentiate patients from controls in at least one disease type. Colors represent the mean difference in editing levels compared to controls. Gray cells represent missing data or differences not meeting the significance cutoff. Significance is defined by the Wilcoxon rank-sum test p-values followed by the Benjamini–Hochberg procedure with FDR < 0.05. | PMC10085048 | pcbi.1010923.g004.jpg |
0.451071 | e8cbc7326e144548b35ef079261263e6 | Construction of nomogram models for thyroid cancer. (A) A nomogram combining the risk score and age. (B) AUC of time-dependent ROC curves evaluated the prognostic capacity of the nomogram. (C–E) Calibration curves comparing the nomogram-predicted (C) 1-, (D) 2-, and (E) 5-year survival and actual survival. | PMC10086330 | fonc-13-1108773-g001.jpg |
0.429427 | 0e8ccc440709430286061004453d0974 | Identification of calcium metabolism related differentially expressed genes. (A) Venn plot of the differentially expressed genes between tumor and normal tissue that were correlated with OS. (B, C) Heatmaps of the differentially expressed genes associated with OS. (D) Forest plot of the results of the univariate Cox regression analysis between gene expression and OS. (E, F) The correlation of the differentially expressed genes associated with OS. | PMC10086330 | fonc-13-1108773-g002.jpg |
0.420309 | 0942ccec5f854957be477f8643554bf4 | Prognostic analysis of the 5-gene signature model. (A) The distribution and median value of the risk scores. (B) The distributions of OS status, OS and risk score. (C) PCA analysis of the TCGA cohort. (D) t-SNE analysis of the TCGA cohort. (E) Kaplan-Meier curves of the OS in the two groups. (F) AUC of time-dependent ROC curves evaluated the prognostic capacity of the risk score. | PMC10086330 | fonc-13-1108773-g003.jpg |
0.429752 | 32bca05650384f9aaea05866d370b987 | Validation of the 5-gene signature model. (A) The distribution and median value of the risk scores. (B) The distributions of OS status, OS and risk scores. (C) PCA analysis of the ICGC cohort. (D) t-SNE analysis of the ICGC cohort. (E) Kaplan-Meier curves of the OS in the two groups. (F) AUC of time-dependent ROC curves evaluated the prognostic capacity of the risk score. | PMC10086330 | fonc-13-1108773-g004.jpg |
0.498815 | 144ca448ecc44ebbbb982256fb53924e | Results of univariate and multivariate Cox regression analysis on OS. (A) Univariate Cox regression analysis on OS. (B) Multivariate Cox regression analysis on OS. | PMC10086330 | fonc-13-1108773-g005.jpg |
0.373526 | b151b34c6126499782cfada3e50d8e14 | Functional enrichment analysis of DEGs. (A) Top 10 biological process (BP) terms, cellular components terms (CC), molecular functions (MF) terms. (B) Top 26 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. | PMC10086330 | fonc-13-1108773-g006.jpg |
0.44766 | 945ba7dc726048538157bc50f4502285 | Comparison of the ssGSEA scores between different risk groups. (A) The scores of 16 immune cells. (B) The scores of 13 immune-related functions. Adjusted P values were showed as: **, P< 0.01; ***, P< 0.001. (C) The association between 7 prognostic calcium metabolism related genes and immune cells. | PMC10086330 | fonc-13-1108773-g007.jpg |
0.440883 | c928370e84d444b08c4142e16fc0be26 | The correlation between gene expression levels and drugs. The top 16 most relevant were visualized. | PMC10086330 | fonc-13-1108773-g008.jpg |
0.480444 | 6e825dffdef3435a9c1b0590bd683827 | Plasma concentration–time profiles for the deuterated α‐HTBZ and β‐HTBZ metabolites in EM and PM cohorts following single doses of 24, 48, and 72 mg of deutetrabenazine. In panels A and B, the mean (standard error) concentrations of α‐HTBZ and β‐HTBZ metabolites are depicted as filled blue squares, green triangles, and orange diamonds for the EM cohort and as open blue squares, green triangles, and orange diamonds for the PM cohort following administration of deutetrabenazine doses 24, 48, and 72 mg, respectively. EM, extensive/intermediate metabolizer; α‐HTBZ, α‐dihydrotetrabenazine; β‐HTBZ, β‐dihydrotetrabenazine; PM, poor metabolizer. | PMC10086964 | CPDD-12-94-g001.jpg |
0.411179 | dc63ca7def4945a095596da55076b8f1 | Model‐predicted ΔΔQTcF (mean and 90%CI) and estimated placebo‐adjusted ΔQTcF (mean and 90%CI) across deciles of plasma concentrations for deuterated α‐HTBZ and β‐HTBZ (concentration‐QTc analysis set). For panel A, the prediction was based on the model ΔQTcF = 0.51 + [concentrations of α‐HTBZ × 6.6E‐7] + [75615 × 0.00004] where 75615 is the arithmetic mean concentration of β‐HTBZ at tmax of α‐HTBZ. In panel B, the prediction was based on the model ΔQTcF = 0.51 + [70657 × 6.6E‐7] + [Concentrations of β‐HTBZ × 0.00004] where 70657 is the arithmetic mean concentration of α‐HTBZ at tmax of β‐HTBZ. The red circles with vertical bars denote the mean placebo‐adjusted ΔQTcF with 90%CI displayed at the median plasma concentration within each decile for deuterated α‐HTBZ (A) and deuterated β‐HTBZ (B). The black circle with vertical bars denotes the time‐adjusted mean ΔQTcF with 90%CI for placebo at a concentration of 0. The solid black line with gray shaded area denotes the model‐predicted mean ΔΔQTcF with 90%CI. The horizontal red line with notches shows the range of concentrations divided into deciles for deuterated α‐HTBZ (A) and deuterated β‐HTBZ (B). The area between each decile represents the point at which 10% of the data is present. Blue diamonds with lines represent the Cmax geometric means and 90%CI at the recommended therapeutic doses, 24 mg twice daily for EM cohort and 18 mg twice daily for the PM cohort. α‐HTBZ, α‐dihydrotetrabenazine; β‐HTBZ, β‐dihydrotetrabenazine; ΔQTcF, change from baseline in QT interval corrected using Fridericia's formula; tmax, time of peak plasma concentration. | PMC10086964 | CPDD-12-94-g002.jpg |
0.382041 | e4b2cb035e8348ee91b9ff392d89a8f0 | Scatterplot of observed α‐HTBZ and β‐HTBZ plasma concentrations and ΔQTcFs. The red line with the blue shaded area denotes the locally estimated scatterplot regression and 90% confidence limits. The black solid line denotes the simple linear regression line. The open black circles, blue squares, green triangles, and orange diamonds denote the pairs of ΔQTcF and observed plasma concentrations of deuterated α‐HTBZ (Panel A) and deuterated β‐HTBZ (Panel B) for placebo, deutetrabenazine 24, 48, and 72 mg dose treatment groups, respectively. α‐HTBZ, α‐dihydrotetrabenazine; β‐HTBZ, β‐dihydrotetrabenazine; LOESS, locally estimated scatterplot. | PMC10086964 | CPDD-12-94-g003.jpg |
0.514284 | a9e9f0ad2f124384a7dbe036e021018d | Least square (LS) mean change‐from‐baseline HR (ΔHR) across time points. LS means based on a linear mixed‐effects model: ΔHR = Time + Treatment + Treatment × Time + Baseline HR + Sequence + Period. A compound symmetry covariance structure was used to specify the repeated measures at postdose time points within subjects. Open black circles, blue squares, green triangles, and orange diamonds represent placebo and deutetrabenazine doses 24, 48, and 72 mg, respectively. EM, extensive/intermediate metabolizer; HR, heart rate; PM, poor metabolizer. | PMC10086964 | CPDD-12-94-g004.jpg |
0.391104 | 7e9d6344c378419fb16c78c6d4c47086 | Boxplots of Cmax and AUCinf values for the deuterated α‐HTBZ and β‐HTBZ metabolites in EM and PM cohorts following single doses of 24, 48, and 72 mg of deutetrabenazine. The horizontal line displays the median, the box edges show the 25th and 75th percentiles, and the whiskers show the smallest and highest value within 1.5 box lengths from the box. Outliers are shown as circles. Open blue, green, and orange boxes represent deuterated α‐HTBZ concentrations following 24, 48, and 72 mg doses, respectively. Filled blue, green, and orange boxes are indicated for deuterated β‐HTBZ concentrations following 24, 48, and 72 mg doses. AUCinf, area under the plasma concentration–time curve from time 0 to infinity; Cmax, maximum plasma concentration; EM, extensive/intermediate metabolizer; α‐HTBZ, α‐dihydrotetrabenazine; β‐HTBZ, β‐dihydrotetrabenazine; PM, poor metabolizer. | PMC10086964 | CPDD-12-94-g005.jpg |
0.417131 | 3a161feef82449399bfa9f6c41e05c88 | Study 17MOIR‐0012 PAS scores vs ALSFRS‐R score. ALSFRS‐R, ALS Functional Rating Scale‒Revised; PAS, Penetration Aspiration Scale. In the figure, the green circles represent patients who improved in their PAS scores from pre‐ to post‐dose, the red circle represents a patient who had a worsened PAS worst score from pre‐dose to post‐dose, and the blue circles represent patients who had no change in PAS scores from pre‐dose to post‐dose. | PMC10087659 | CPDD-12-57-g001.jpg |
0.368108 | 7b5cf751c6c548399b3f2cb029b8694d | Study 162020 design. ROF, riluzole oral film. | PMC10087659 | CPDD-12-57-g002.jpg |
0.519336 | 90f7e0ebc6c7432ea9e1a37d2f139538 | Study 162020 riluzole plasma concentration–time curves (mean ± SD values shown). (A) Treatments A and B, ROF compared with riluzole tablets under fasting conditions. (B) Treatments A and C, ROF under fasting vs high‐fat meal conditions. ROF, riluzole oral film. | PMC10087659 | CPDD-12-57-g003.jpg |
0.430908 | 15b9859ea4014c80b00e9f913206b707 | PRISMA flow diagram illustrating selection of studies. | PMC10087740 | ActaO-94-11958-g001.jpg |
0.43766 | 91e1709ea4704ac0abb1f1411b95dbbe | Random-effects meta-analysis on the effect of precautions on the risk of early dislocations after total hip arthroplasty. Abbreviations: M-H = Mantel-Haenszel, CI = confidence interval, RCT = randomized controlled trial NRS = non-randomized study. | PMC10087740 | ActaO-94-11958-g002.jpg |
0.418852 | ec93f219b9fe4ef7920f949d9fc251e4 | Different cytokine expression levels in GCF of 3 units of FPDs and dental implants | PMC10088209 | 13005_2023_359_Fig1_HTML.jpg |
0.450573 | 6c8c6d59449447729257d0b386c063df | The molecular structure of (I)–(IV), with non-H atoms labeled and 50% probability displacement ellipsoids for non-H atoms. Hydrogen bonds drawn as dashed lines. Disorder omitted for clarity. | PMC10088315 | e-79-00386-fig1.jpg |
0.444012 | 7f1b7cdbd82f489b842e5b639d406c06 | Packing of the structures of this report. (I), (IV): view slightly inclined to the b axis·(II), (III): view approximately along the a axis. Disorder omitted for clarity. | PMC10088315 | e-79-00386-fig2.jpg |
0.457081 | 19d8039ec1794b059c5160b389fd3ad2 | The morphologies of the samples used to obtain structures for this report and the result of BFDH calculations based on the structures. | PMC10088315 | e-79-00386-fig3.jpg |
0.525941 | 97933cd0aebe47f890e7ccd688f53380 | CONSORT diagram: participant flow. | PMC10089325 | pntd.0011236.g001.jpg |
0.398829 | 901e38334b4745a096d244763161a0f7 | Number and percentage of participants experiencing solicited injection site events after any dose of vaccine by event, maximum severity, and vaccine group. | PMC10089325 | pntd.0011236.g002.jpg |
0.433475 | d22ad52cdfc34c3bb1aee4ba90f0d31a | Number and percentage of participants experiencing solicited systemic events after any dose of vaccine by event, maximum severity, and vaccine group. | PMC10089325 | pntd.0011236.g003.jpg |
0.442242 | 20bc8ac717a343a2856b66afe39bd3be | Geometric mean anti-Sm-TSP-2 IgG levels over time by vaccine group, as measured by ELISA (Arbitrary Units).Per-protocol immunogenicity population. Vaccinations were administered on study days 1, 57, and 113. Error bars represent 95% confidence intervals. Euvax B hepatitis B recipients were pooled across cohorts. | PMC10089325 | pntd.0011236.g004.jpg |
0.455621 | eb513534b2f74adfbfcccc51eea499a9 | Fold change from baseline in anti-Sm-TSP-2 IgG levels at study day 127 by vaccine group.Per-protocol immunogenicity population. Vaccinations were administered on study days 1, 57, and 113. Error bars represent 95% confidence intervals. Euvax B hepatitis B recipients were pooled across cohorts. | PMC10089325 | pntd.0011236.g005.jpg |
0.487636 | 2cf2cf57d50d4d3d96edc61092fbb86a | Geometric mean anti-Sm-TSP-2 IgG subclass responses over time by vaccine group, as measured by ELISA (Arbitrary Units): A) IgG1, B) IgG3, C) IgG4. (Per-protocol immunogenicity population). Note: Vaccinations were administered on study days 1, 57, and 113. Error bars represent 95% confidence intervals. Euvax B hepatitis B recipients were pooled across cohorts. | PMC10089325 | pntd.0011236.g006.jpg |
0.479585 | 819e774692b74aeb97738b4ee09b6920 |
(
A
) Expandable cage with multiple sharp teeth on both ends, these sharp teeth anchored in adjacent vertebral end plates. (
B
) Expandable cage with blunt end (without sharp teeth). (
C
) Cervical plate with screws.
| PMC10089757 | 10-1055-s-0043-1761238-i2280006-1.jpg |
0.404215 | ec32e11f0da348d2ba6ae01793921e9b |
(
A
) Preoperative evaluation of cervical lordosis and kyphotic deformity by measurement of the C2-C7 Cobb's angle. (
B
) Postoperative evaluation of correction of cervical lordosis and kyphotic deformity by measurement of the C2-C7 Cobb's angle. (
C
) Multiple level corpectomy with anterior cervical plate; well-placed expandable cage and plate showing fusion; 1-anterior cervical plate with variable angle screws, 2-expandable cage. (
D
) expandable cage subsidence at lower end plate (
white arrow
).
| PMC10089757 | 10-1055-s-0043-1761238-i2280006-2.jpg |
0.530981 | 3485dfafb5b942bba0bf825acffdc236 | FT-IR spectra of (a) boehmite, (b) boehmite@CPTMS, (c) bis(PYT)@boehmite and (d) Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig10_HTML.jpg |
0.389685 | cb983a68d0b146378e33bb674a9d0b0e | The general method used to synthesize 5-substituted 1H-tetrazoles in presence of Sm-bis(PYT)@boehmite nanocatalyst. | PMC10090185 | 41598_2023_33109_Fig11_HTML.jpg |
0.495261 | cefea2dc5e444179bf18eabed6f59959 | Homoselectivity of Sm-bis(PYT)@boehmite in the synthesis of 5-substituted 1H-tetrazoles from [3 + 2] cycloaddition of NaN3 with dicyano substituted derivatives. | PMC10090185 | 41598_2023_33109_Fig12_HTML.jpg |
0.537834 | 79028ad52c7040688b8d85a160823c68 | An expected mechanism for synthesizing 5-substituted 1H-tetrazoles in the presence of Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig13_HTML.jpg |
0.384971 | de29ff26c0904adcbd1765d41bc99267 | The recoverability and reusability of Sm-bis(PYT)@boehmite nanocatalyst in the synthesis of 5-phenyl-1H-tetrazole. | PMC10090185 | 41598_2023_33109_Fig14_HTML.jpg |
0.482167 | 7c0ee34d68f8440c8a58ff0220828ad0 | The powder XRD pattern of recovered Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig15_HTML.jpg |
0.398816 | e5a7bc484e634e7d9b728b78ffaaff14 | FESEM images of recovered Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig16_HTML.jpg |
0.396799 | 9f840766267b440b90edefcb5efefecb | EDS diagram of recovered Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig17_HTML.jpg |
0.413453 | 7442dc71d87a4dc69377e573c5d4630f | Elemental mapping of (a) Al, (b) Si, (c) O, (d) C, (e) S, (f) N and (g) Sm for recovered Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig18_HTML.jpg |
0.484161 | 41ad1d000d7441bdbf7e5f5bfa306176 | FT-IR spectra of (a) Sm-bis(PYT)@boehmite and (b) recovered Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig19_HTML.jpg |
0.427263 | e873c6f6c1bf466c9d2a575f99620f8f | Synthesis of Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig1_HTML.jpg |
0.547697 | c37e831fd74e4e9581b8bce8954ee68e | SEM images of Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig2_HTML.jpg |
0.428139 | 4f350debbc2146d89124b06df4b5bf36 | DLS analysis of Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig3_HTML.jpg |
0.388148 | e5a24f8be3a84b2099f6dff1f10bbe3e | EDS diagram of Sm-bis(PYT)@boehmite. | PMC10090185 | 41598_2023_33109_Fig4_HTML.jpg |
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